Deep Learning-based Estimation for Multitarget Radar Detection

This work presents a deep-learning approach to multitarget radar detection and parameter estimation. The proposed neural architecture handles target multiplicity directly, achieving robust detection performance in propagation conditions that challenge classical multi-hypothesis radar detectors.

Recommended citation: M. Delamou, A. Bazzi, M. Chafii and E. M. Amhoud, "Deep Learning-based Estimation for Multitarget Radar Detection," in 2023 IEEE 97th Vehicular Technology Conference (VTC2023-Spring), Florence, Italy, 2023, pp. 1-5. https://ieeexplore.ieee.org/document/10200157

@article{delamou2023deep,
  title   = {Deep Learning-based Estimation for Multitarget Radar Detection},
  author  = {Mamady Delamou and Ahmad Bazzi and Marwa Chafii and El Mehdi Amhoud},
  journal = {2023 IEEE 97th Vehicular Technology Conference (VTC2023-Spring)},
  pages   = {1--5},
  year    = {2023},
  month   = {jun},
  publisher = {IEEE},
  doi     = {10.1109/VTC2023-Spring57618.2023.10200157},
  url     = {https://doi.org/10.1109/VTC2023-Spring57618.2023.10200157},
  eprint  = {2305.05621},
  archivePrefix = {arXiv},
}